Senior Data Science, AI & Analytics Engineer

About the role

This is a hands-on technical role responsible for designing, developing, and supporting artificial intelligence, intelligent automation, data engineering, analytics, and operational intelligence solutions across Clean Energy Fuels. The successful candidate will work across the full solution lifecycle—from business requirements and architecture through development, deployment, and support—to deliver scalable solutions that improve operational visibility, automate business processes, enhance reporting capabilities, and enable data-driven decision making.

This role combines data engineering, AI enablement, cloud technologies, enterprise integrations, operational intelligence, and IoT analytics to solve complex business challenges across multiple functions of the organization. You will help build solutions that support hundreds of connected assets, operational facilities, business processes, and decision-makers across North America.

Responsibilities

• Data Engineering, Integration & Intelligent Automation
  • Design, develop, and maintain scalable data pipelines, enterprise data products, APIs, integrations, and analytics solutions using Azure Databricks, SQL, Python, and cloud-based technologies.
  • Develop and support data integration frameworks connecting ERP systems, operational platforms, financial applications, IoT devices, external systems, and third-party data providers.
  • Design and maintain secure API-based integrations that enable efficient data exchange across enterprise applications and business processes.
  • Develop trusted, reusable, and governed datasets that support reporting, analytics, AI, automation, and operational intelligence initiatives.
  • Implement modern data engineering practices including data quality validation, automated testing, monitoring, observability, lineage tracking, and performance optimization.
  • Improve scalability, reliability, maintainability, and security of enterprise data and analytics platforms.
  • Modernize manual, spreadsheet-based, and legacy business processes through automation and cloud-based solutions.
• AI & Intelligent Automation
  • Design, develop, and support AI-enabled solutions that improve productivity, operational efficiency, and business decision-making.
  • Build intelligent automation workflows using Generative AI, machine learning, AI agents, APIs, workflow orchestration, and enterprise data platforms.
  • Develop AI-powered assistants, custom copilots, recommendation engines, knowledge solutions, and decision-support capabilities.
  • Integrate AI services and intelligent automation into enterprise applications, reporting solutions, and operational workflows.
  • Develop predictive analytics, intelligent auditing, anomaly detection, forecasting, optimization, and recommendation solutions.
  • Identify opportunities to reduce manual effort through automation and AI-driven process transformation.
  • Collaborate with business stakeholders to evaluate, prioritize, and implement high-value AI initiatives.
  • Support AI governance, monitoring, testing, and continuous improvement to ensure scalable and responsible AI adoption.
• IoT & Operational Intelligence
  • Design and support data pipelines and analytics solutions that leverage IoT, telemetry, operational, and industrial data sources.
  • Develop near real-time operational monitoring, alerting, and intelligence capabilities that improve visibility into business and field operations.
  • Support predictive maintenance, condition-based monitoring, asset performance management, and operational optimization initiatives.
  • Build scalable streaming and event-driven data solutions capable of processing high-volume operational and telemetry data.
  • Develop dashboards, analytics, and operational intelligence solutions that provide visibility into asset health, utilization, reliability, performance trends, and business KPIs.
  • Collaborate with Operations, Engineering, and business teams to identify opportunities to improve efficiency, reduce downtime, and optimize performance through data, AI, and automation.
  • Support the evolution of connected asset, digital operations, and industrial intelligence capabilities across Clean Energy's fueling and operational network.
• Data Governance & Quality
  • Support enterprise data governance, reporting certification, and data quality initiatives.
  • Develop automated monitoring, validation, reconciliation, and exception-reporting capabilities.
  • Assist with metadata management, lineage tracking, documentation, and governance practices.
  • Partner with business stakeholders to improve the accuracy, consistency, reliability, and trustworthiness of enterprise data assets.
• Business Intelligence & Analytics
  • Power BI development, including semantic model and dataset development, DAX, Power Query, dashboard design, and optimization.
  • Reporting automation and self-service analytics.
• Solution Delivery
  • Translate business requirements into practical and scalable technical solutions.
  • Participate in all phases of solution delivery including discovery, design, development, testing, deployment, and production support.
  • Collaborate closely with cross-functional teams to ensure solutions align with business objectives.
  • Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives.

Requirements

• Data Engineering & Integration
  • Advanced SQL development and optimization.
  • Strong Python programming skills.
  • ETL/ELT pipeline design and development.
  • API design, integration, and data exchange patterns.
  • Data modeling and transformation techniques.
  • Structured and semi-structured data processing.
• Power BI
  • Power BI development and administration.
  • Semantic model development.
  • DAX and Power Query.
• Cloud & Analytics Platforms
  • Azure Databricks.
  • Delta Lake and Lakehouse architecture.
  • Unity Catalog.
  • Databricks Workflows.
  • Cloud-based storage and integration technologies.
  • Azure DevOps, DataOps, CI/CD, and platform automation.
• Artificial Intelligence & Automation
  • Generative AI technologies and AI-assisted workflows.
  • AI agents, copilots, intelligent automation, and workflow orchestration.
  • Machine learning and predictive analytics.
  • Statistical analysis and data science methodologies.
  • Model deployment, monitoring, and lifecycle management.
• IoT & Operational Analytics
  • IoT, telemetry, industrial, or operational data environments.
  • Streaming and near real-time data processing.
  • Operational intelligence and monitoring solutions.
  • Predictive maintenance and asset monitoring.
• Professional Competencies
  • Ability to independently manage technical workstreams from concept through deployment and support.
  • Strong organizational skills with the ability to manage multiple priorities simultaneously.
  • Focus on delivering business value through practical and scalable solutions.
  • Ability to translate complex or ambiguous business requirements into actionable technical solutions.
  • Strong analytical and troubleshooting skills across data, analytics, and platform environments.
  • Comfortable working across both technical and business domains.
  • Effective communication with technical and non-technical audiences.
  • Strong stakeholder engagement and relationship-building skills.
  • Collaborative approach to solution development and problem solving.
  • Proactively identifies opportunities to improve automation, efficiency, data quality, and reporting capabilities.
  • Maintains awareness of emerging technologies, analytics techniques, and AI capabilities.
  • Committed to learning, innovation, and continuous improvement.

Qualifications

• Required
  • 7–10+ years of experience with enterprise-scale data platforms, cloud analytics architecture, API integration development, advanced SQL, and Python.
• Preferred
  • Power BI administration and governance experience.
  • PySpark and distributed processing experience.
  • Data governance and data quality experience.
  • Experience supporting AI and machine learning solutions.
  • IoT, telemetry, or operational analytics experience.
  • Experience with enterprise data modernization initiatives.

Pay

$140,000 - $150,000 for well-qualified candidates.

About Clean Energy Fuels

Clean Energy Fuels is North America's largest provider of renewable natural gas (RNG) and alternative fueling solutions for the transportation industry. We operate a nationwide network of fueling infrastructure that supports fleets across transit, trucking, municipal services, airports, waste management, and other critical industries.

At Clean Energy Fuels, we are investing in next-generation analytics, AI, Industrial IoT, cloud platforms, and intelligent automation to improve operational performance, increase reliability, enhance decision-making, and support our mission of delivering cleaner transportation energy solutions.

This role offers the opportunity to work on meaningful business challenges using AI, analytics, automation, and IoT technologies that directly impact real-world operations, sustainability initiatives, and critical infrastructure across North America. You'll work at the intersection of artificial intelligence, intelligent automation, industrial IoT, operational intelligence, advanced analytics, cloud data platforms, and modern data engineering.